Splunk Groupby: Examples with Stats
20 Feb 2021 Examples on how to do aggregate operations on Splunk using the stats and timechart commands.
Read More ›Python Datetime with Timezones: Examples and Reference
03 Jan 2021 Examples on how to work with datetimes and timezones, using the standard python library, datetime.
Read More ›Splunk Examples: Timecharts
19 Dec 2020 Examples and reference for common configurations and use cases for the splunk timechart directive
Read More ›Suppressing, Ignoring Warnings in Python: Reference and Examples
11 Nov 2020 Examples on how to suppress warnings in python code, when needed. Can be used in standalone scripts, structured systems and/or jupyter notebooks.
Read More ›Pull-Requests: Best Practices and Lessons Learned
12 Oct 2020 Some tips and lessons learned on creating useful and pleasant PRs that are easy to review. Also some best practices on interacting with reviewers and peers in general.
Read More ›software-engineering software-architecture
On Rolling out Backwards-Compatible Software Upgrades
10 Oct 2020 Thoughts on how to deal with problems that arise from legacy systems that have grown too much;
Read More ›Pandas Dataframes: Apply Examples
26 Sep 2020 Examples on how to use pandas apply, on columns, dataframes, etc, with best practices and warnings about performance.
Read More ›Python: Working with Paths & the Filesystem
26 Sep 2020 Several examples on how to work with paths and files in python, convert from relative to aboslute paths, check if a path points to a valid file, etc.
Read More ›product-management data-science data-products
11 Types of Data Products, with Examples
22 Sep 2020 Here is a list of data products you can build using various types of data science methods. Includes use cases and main techniques for each.
paper-summary natural-language-processing sequence-learning transformer-architecture
Paper Summary: Improving Language Understanding by Generative Pre-Training
11 Sep 2020 Summary of the 2018 article "Improving Language Understanding by Generative Pre-Training" by Radford et al.